ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.08894
19
53
v1v2 (latest)

Acquisition of Channel State Information for mmWave Massive MIMO: Traditional and Machine Learning-based Approaches

16 June 2020
Chenhao Qi
Peihao Dong
Wenyan Ma
Hua Zhang
Zaichen Zhang
Geoffrey Ye Li
ArXiv (abs)PDFHTML
Abstract

The accuracy of available channel state information (CSI) directly affects the performance of millimeter wave (mmWave) communications. In this article, we provide an overview on CSI acquisition including beam training and channel estimation for mmWave massive multiple-input multiple-output systems. The beam training can avoid the estimation of a large-dimension channel matrix while the channel estimation can flexibly exploit advanced signal processing techniques. After discussing the traditional and machine learning-based approaches in this article, we compare different approaches in terms of spectral efficiency, computational complexity, and overhead.

View on arXiv
Comments on this paper